Studies on the evolution of alkali silicate in a simulated alkali-silica reaction system

In this study, the interaction between the reactive silica present in aggregates and the alkalis and hydroxyls present in the pore solution of cement paste is simulated in a chemical model system and investigated experimentally. Various properties of the solid and liquid phases are investigated. The results show that the nano and micro structure and properties of the formed alkali silicate change significantly during this process

Diagnosis of Lung Cancer: What Metabolomics Can Contribute

The reprogrammed metabolism of cancer cells reflects itself in an alteration of metabolite concentrations, which in turn can be used to define a specific metabolic phenotype or fingerprint for cancer. In this contribution, a metabolism-based discrimination between lung cancer patients and healthy controls, derived from an analysis of human blood plasma by proton nuclear magnetic resonance (1H-NMR) spectroscopy, is described. This technique is becoming widely used in the field of metabolomics because of its ability to provide a highly informative spectrum, representing the relative metabolite concentrations. Cancer types are characterized by decreased or increased levels of specific plasma metabolites, such as glucose or lactate, compared to controls. Data analysis by multivariate statistics provides a classification model with high levels of sensitivity and specificity. Nuclear magnetic resonance (NMR) metabolomics might not only contribute to the diagnosis of lung cancer but also shows potential for treatment follow-up as well as for paving the way to a better understanding of disease-related diverting biochemical pathways

Pola Pemanfaatan Lahan dan Faktor-faktor Perkembangan Wilayah Perkotaan di Kabupaten Sleman dan Kabupaten Bantul

Penelitian ini bertujuan untuk menganalisis pertumbuhan wilayah perkotaan, terutama dinamika wilayah periurban yang menjadi target perluasan aktivitas perkotaan, terutama permukiman. Fenomena urbanisasi kontemporer ini terjadi akibat migrasi kelompok ekonomi menengah ke pinggiran kota seiring dengan meningkatnya kepadatan pusat kota yang berdampak pada penurunan kualitas lingkungan hidup. Keinginan untuk mencari lingkungan permukiman yang lebih baik merupakan faktor pendorong utama, di samping keterbatasan lahan permukiman di pusat kota. Hasil yang didapat menunjukkan bahwa perambahan lahan di wilayah periurban telah merubah struktur ruang dan pola pemanfaatan lahan. Pada dimensi ekonomi, perkembangan aktivitas perkotaan di wilayah periurban telah memicu pergeseran struktur ekonomi primer yang berbasis potensi agraris menuju sektor jasa dan perdagangan akibat perubahan struktur sosial

Charge-discharge characteristics of textile energy storage devices having different PEDOT:PSS ratios and conductive Yarns configuration

Conductive polymer PEDOT:PSS, sandwiched between two conductive yarns, has been proven to have capacitive behavior in our textile energy storage devices. Full understanding of its underlying mechanism is still intriguing. The effect of the PEDOT to PSS ratio and the configuration of the electrode yarns are the focus of this study. Three commercial PEDOT:PSS yarns, Clevios P-VP-AI-4083, Ossila AI 4083, and Orgacon ICP 1050, as well as stainless steel and silver-coated polybenzoxazole (Ag/PBO) yarns, in various combinations, were used as solid electrolytes and electrodes, respectively. Analyses with NMR, ICP-OES, TGA, and resistivity measurement were employed to characterize the PEDOT:PSS. The device charge-discharge performance was measured by the Arduino microcontroller. Clevios and Ossila were found to have identical characteristics with a similar ratio, that is, 1:5.26, hence a higher resistivity of 1000 Ω.cm, while Orgacon had a lower PEDOT to PSS ratio, that is, 1:4.65, with a lower resistivity of 0.25⁻1 Ω.cm. The thermal stability of PEDOT:PSS up to 250 °C was proven. Devices with PEDOT:PSS having lower conductivity, such as Clevios P-VP-AI-4083 or Ossila AI 4083, showed capacitive behavior. For a better charge-discharge profile, it is also suggested that the PEDOT to electrode resistance should be low. These results led to a conclusion that a larger ratio of PEDOT to PSS, having higher resistivity, is more desirable, but further research is needed

Repeatability of two semi-automatic artificial intelligence approaches for tumor segmentation in PET

Background: Positron emission tomography (PET) is routinely used for cancer staging and treatment follow-up. Metabolic active tumor volume (MATV) as well as total MATV (TMATV—including primary tumor, lymph nodes and metastasis) and/or total lesion glycolysis derived from PET images have been identified as prognostic factor or for the evaluation of treatment efficacy in cancer patients. To this end, a segmentation approach with high precision and repeatability is important. However, the implementation of a repeatable and accurate segmentation algorithm remains an ongoing challenge. Methods: In this study, we compare two semi-automatic artificial intelligence (AI)-based segmentation methods with conventional semi-automatic segmentation approaches in terms of repeatability. One segmentation approach is based on a textural feature (TF) segmentation approach designed for accurate and repeatable segmentation of primary tumors and metastasis. Moreover, a convolutional neural network (CNN) is trained. The algorithms are trained, validated and tested using a lung cancer PET dataset. The segmentation accuracy of both segmentation approaches is compared using the Jaccard coefficient (JC). Additionally, the approaches are externally tested on a fully independent test–retest dataset. The repeatability of the methods is compared with those of two majority vote (MV2, MV3) approaches, 41%SUVMAX, and a SUV > 4 segmentation (SUV4). Repeatability is assessed with test–retest coefficients (TRT%) and intraclass correlation coefficient (ICC). An ICC > 0.9 was regarded as representing excellent repeatability. Results: The accuracy of the segmentations with the reference segmentation was good (JC median TF: 0.7, CNN: 0.73). Both segmentation approaches outperformed most other conventional segmentation methods in terms of test–retest coefficient (TRT% mean: TF: 13.0%, CNN: 13.9%, MV2: 14.1%, MV3: 28.1%, 41%SUVMAX: 28.1%, SUV4: 18.1%) and ICC (TF: 0.98, MV2: 0.97, CNN: 0.99, MV3: 0.73, SUV4: 0.81, and 41%SUVMAX: 0.68). Conclusion: The semi-automatic AI-based segmentation approaches used in this study provided better repeatability than conventional segmentation approaches. Moreover, both algorithms lead to accurate segmentations for both primary tumors as well as metastasis and are therefore good candidates for PET tumor segmentation

Biochar characterization of raw versus spent common ivy: Inorganic nutrient behavior

Hedera sp., common Ivy, a lignocellulosic evergreen vine, is commonly seen in gardens and yards all over the globe. It is an excellent candidate to be applied in vertical green walls to improve ecosystems in future green cities (e.g. fine particulate matter adsorption). These green walls need to be trimmed regularly, thus leaving a major residue stream which could be promising as biomass feedstock for biochar fertilizer production. However, common Ivy contains valuable compounds (e.g. etheric oils and triterpene saponins) increasing the process’ added value. These should preferably be extracted prior to thermal conversion. The aim of this study is therefore to investigate the influence of extraction methods on the final properties of common ivy’s biochar using conventional pyrolysis. Investigated extraction methods include a Soxhlet ethanol extraction and a steam distillation, to obtain respectively a triterpene saponin and volatile oil extract. The influence of these extractions on the biochar properties was studied by comparing the thermal conversion and biochar properties of spent, extracted, biomass with raw biomass. Studied properties include biochar yield, elemental composition (CHNO), amount of inorganic nutrients, specific surface area, and presence of harmful heavy metals. The guidelines of the European Biochar Certificate are used to evaluate said properties. Furthermore, the pyrolysis process parameters, temperature and heating rate, were optimized to improve said biochar properties for application as fertilizer. Tested pyrolysis temperatures were 400, 550 and 700 °C. Results show that biochar yield from raw ivy was inversely proportional with pyrolysis temperature ranging from 29.6 ± 0.6% at 400 °C, 25.4% ± 0.03 at 550 °C and 23.0 ± 0.06 % at 700 °C. It was found that steam distillation lowers the amount of heavy metals in the material, whilst the inorganic nutrients are retained, thus enhancing the biochar’s potential as fertilizer. Furthermore, nitrogen content remained constant, around 2%, before and after pyrolysis both for raw and spent ivy, these results indicate that high-quality biochars were produced. To further understand biochar’s chemical behavior in soils, structural properties and morphology are being investigated further, specific surface area via BET, general pore structure using SEM, surface functional groups with FT-IR and, aromaticity with CP/MAS 13C NMR results will be presented accordingly

Photocatalytic Performance of Undoped and Al-Doped ZnO Nanoparticles in the Degradation of Rhodamine B under UV-Visible Light:The Role of Defects and Morphology

Quasi-spherical undoped ZnO and Al-doped ZnO nanoparticles with different aluminum content, ranging from 0.5 to 5 at% of Al with respect to Zn, were synthesized. These nanoparticles were evaluated as photocatalysts in the photodegradation of the Rhodamine B (RhB) dye aqueous solution under UV-visible light irradiation. The undoped ZnO nanopowder annealed at 400 °C resulted in the highest degradation efficiency of ca. 81% after 4 h under green light irradiation (525 nm), in the presence of 5 mg of catalyst. The samples were characterized using ICP-OES, PXRD, TEM, FT-IR, 27Al-MAS NMR, UV-Vis and steady-state PL. The effect of Al-doping on the phase structure, shape and particle size was also investigated. Additional information arose from the annealed nanomaterials under dynamic N2 at different temperatures (400 and 550 °C). The position of aluminum in the ZnO lattice was identified by means of 27Al-MAS NMR. FT-IR gave further information about the type of tetrahedral sites occupied by aluminum. Photoluminescence showed that the insertion of dopant increases the oxygen vacancies reducing the peroxide-like species responsible for photocatalysis. The annealing temperature helps increase the number of red-emitting centers up to 400 °C, while at 550 °C, the photocatalytic performance drops due to the aggregation tendency